We have an exciting and rewarding opportunity for you to take your software engineering career to the next level. 

As a Software Engineer III, Machine Learning and AWS at JPMorgan Chase within the Consumer and Community Banking Risk and Fraud team, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives.

Job responsibilities

Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems Identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture  Designs and sets up Machine Learning platform infrastructure to develop and train machine learning models for Risk and Fraud Sets up ML tools on AWS infrastructure through automated pipeline and using Terraform (Infrastrucure as Code) Designs and develops tools to Support machine learning platform for critical CCB Risk and Fraud models Implements performance tuning EMR jobs and best practices in spark job development Enables distributed machine learning techniques on Xgboost, TensorFlow, Scikit learning using EMR RAPIDS, Spark, Dask and Sagemaker

Required qualifications, capabilities, and skills

Formal training or certification on software engineering concepts and 3+ years applied experience Hands-on practical experience in system design, application development, testing, and operational stability Proficient in coding in one or more languages including Python Hands-on experience using Large Language Model tools Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages Demonstrated knowledge of software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.) Hands on experience in AWS-EC2, S3, EMR and Sagemaker to migrate the machine learning models from Hadoop to AWS. Should have good understanding and knowledge in planning and managing AWS Cloud infrastructure and enabling necessary platform security by using best in class Cloud Security Solutions Hands on experience in migrating Spark applications from Big Data Hadoop platform to AWS Cloud using AWS EMR, S3 Buckets, EBS, Lambda and EC2 Instances Hands on experience in application development using EC2, S3, EMR, Lamdba. Provision AWS resources into multiple cloud accounts through automated pipeline using Terraform Experience in the AWS platform monitoring tools like Cloudwatch, Datadog for monitoring the utilization and in setting up the thresholds and performance alerts Hands on experience in developing automation scripts using Python and Unix Shell Scripting

Preferred qualifications, capabilities, and skills

Previous experience with modern front-end technologies Experience in the design, implementation, and support of advanced machine learning tools such as Anaconda packages, XGboost, Scipy, numPy, Pandas, and Tensorflow to support model development